Methods and systems for identifying a particle using dielectrophoresis

ABSTRACT

A system for identifying a particle. The system includes a microfluidic device; a microelectrode array including a plurality of electrodes, the microelectrode array disposed within the microfluidic device; a plurality of particles suspended in a solution and delivered to the micro-electrode array using the microfluidic device; a signal generator operatively coupled to the microelectrode array; a particle detector adjacent to the microelectrode array; and a controller in operative communication with the signal generator and the particle detector. The controller is configured to apply an oscillating voltage signal to the microelectrode array between a low frequency and a high frequency at a sweep rate, wherein the sweep rate is no more than a maximum sweep rate, and determine a distribution of the plurality of particles relative to the microelectrode array at a plurality of frequency levels between the low frequency and the high frequency.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to co-pending U.S. Provisional PatentApplication No. 61/887,178 filed on Oct. 4, 2013, the entire content ofwhich is incorporated herein by reference.

STATEMENT REGARDING FEDERALLY-SPONSORED RESEARCH OR DEVELOPMENT

The present invention was conceived while performing work under CBET0644538, CBET 1041338, and IIP 1340126, each of which has been awardedby the National Science Foundation. The government has certain rights inthe invention.

INTRODUCTION

The present invention relates to identification of particles based ondielectrophoretic responses.

SUMMARY OF THE INVENTION

In one embodiment, a system for identifying a particle includes amicrofluidic device; a microelectrode array including a plurality ofelectrodes, the microelectrode array disposed within the microfluidicdevice; a plurality of particles suspended in a solution and deliveredto the microelectrode array using the microfluidic device; a signalgenerator operatively coupled to the microelectrode array; a particledetector adjacent to the microelectrode array; and a controller inoperative communication with the signal generator and the particledetector. The controller is configured to apply an oscillating voltagesignal to the microelectrode array between a low frequency and a highfrequency at a sweep rate, wherein the sweep rate is no more than amaximum sweep rate, and determine a distribution of the plurality ofparticles relative to the microelectrode array at a plurality offrequency levels between the low frequency and the high frequency.

In another embodiment, a method of identifying a particle. The methodincludes the steps of: placing a plurality of particles adjacent amicroelectrode array, the microelectrode array including a plurality ofelectrodes; applying an oscillating voltage signal to the microelectrodearray, the oscillating voltage signal varying between a low frequencyand a high frequency at a sweep rate, wherein the sweep rate is no morethan a maximum sweep rate; and determining a distribution of theplurality of particles relative to the microelectrode array at aplurality of frequency levels between the low frequency and the highfrequency.

Other features and aspects of the invention will become apparent byconsideration of the following detailed description and accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows (a) Dielectric relaxation mechanism for PS beads showingcases when i) particle polarization occurs at a static frequency, ii)τ_(MW) is shorter than the slow frequency sweep rate (τΔ_(FS)) allowingthe bead interface time to polarize in response to the non-uniform ACfield, and iii) τ_(MW) is longer than the τΔ_(FS) for fast frequencysweep rates and the bead interface does not have time to fully polarize.(b) Schematic of the quadrapole electrodes micro patterned onto a glassslide, and (c) microdevice with PDMS fluidic layer bonded above thequadrapole electrodes silver-epoxied to copper leads.

FIG. 2 shows (a) nDEP behavior of 6 μm PS beads suspended in E-pure H₂O2.5×10⁻⁴ S/m and 250V_(pp)/cm 0.0063, 0.056 and 0.17 MHz/s sweep ratesfrom 0.010 MHz to 1.0 MHz. (b) Raw intensity (arbitrary units) profileof PS beads in the center nDEP region (boxes shown at 0.20 MHz) at0.0063 MHz/s sweep rate. Inset is a calibration of intensity per bead.(c) Clausius-Mossotti factor for the PS beads from 0.010 MHz to 2.0 MHzat three conductivities of 2.5×10⁻⁴, 1.0×10⁻³, and 1.0 S/m. PS beadassembly at slower frequency sweep rates track static frequencyresponses while 0.056 MHz/s illustrates transitional behavior andfrequency sweeps above 0.17 MHz/s substantially lag the true staticfrequency DEP responses.

FIG. 3 shows (a) 6 μm PS beads nDEP intensity profiles for 0.00080,0.0063, and 0.056 MHz/s and static steady state (SS) measurements (blackdiamonds). Intensity analysis captures bead assembly to the quadrapolecenter with transient and SS regions. The slowest frequency sweep rateof 0.00080 MHz/s best predicts the static DEP responses. (b) Beadassembly intensity (arbitrary units) profiles for 0.0063 (n=8) and 0.17MHz/s (n=7) with 95% confidence upper and lower limits shown as dashedlines. (c) Transient slope comparison for static frequencies (0 MHz/s)as well as frequency sweeps. (d) Comparison of static frequency andfrequency sweep PS bead velocities from 0 to 50 s. 0.00080 MHz/s resultsare consistently similar to the static frequency results.

FIG. 4 shows (a) nDEP behavior of RBCs suspended in 0.1 S/m dextrosebuffer and 250V/cm at 0.00080 MHz/s, 0.0063 MHz/s and 0.056 MHz/s sweeprates from 0.010 MHz to 0.50 MHz. (b) RBCs nDEP intensity (arbitraryunits) profiles for 0.00080, 0.0063, and 0.056 MHz/s and staticmeasurements. (c) 0.00080 and 0.056 MHz/s RBC assembly intensity(arbitrary units) profiles n=8, with 95% confidence interval upper andlower limits shown as dashed lines.

FIG. 5 shows an image comparison of the nDEP and pDEP behavior of A+ redblood cells suspended in 0.10 S/m dextrose solution and 1000V_(pp)/cm at0.00080, 0.0016, and 0.0028 MHz/s sweep rates from 0.010 MHz to 1.0 MHz.(1) Denotes red blood cells nDEP behavior and (2) denotes red blood cellpDEP behavior. The red blood cells' DEP behavior at slower frequencysweep rates correlates well with the static frequency response (toprow).

FIG. 6 illustrates (a) nDEP and (b) pDEP intensity profiles for 0.00080,0.0016, and 0.0028 MHz/s and static steady state measurements (solidcircle). The intensity (arbitrary units) analysis captures the RBCsassembly toward the electrode center (nDEP) and near the electrodes(pDEP). 0.00080 MHz/s is the slowest and 0.0016 MHz/s is the fastestsweep rate to best predict RBCs' static DEP response.

FIG. 7 illustrates (a) RBC static images (top row) compared to RBCsresponse using 0.0024 MHz/s (middle and bottom row). R1 and R2 arc twodifferent repeats completed for this measurement. (b) nDEP and (c) pDEPintensity (arbitrary units) profiles for 0.0024 MHz/s with RBC staticsteady state measurements (circles). The images and intensity profilesshow the threshold frequency sweep rate at which agreement with staticmeasurements is acceptable, but begins to falter. Sweep rates less than0.0024 MHz/s agree well. Each test was completed with A+ blood in 0.10S/m at 1000V_(pp)/cm.

FIG. 8 illustrates (a) RBC static images (top row) compared to RBCsresponse using 0.0025 MHz/s (middle and bottom row). R1 and R2 are twodifferent repeats completed for this measurement. (b) nDEP and (c) pDEPintensity profiles for 0.0025 MHz/s with RBC static steady statemeasurements (circles). The images and intensity profiles show pooragreement with static measurements. Each test was completed with A+blood in 0.10 S/m at 1000V_(pp)/cm.

FIG. 9 illustrates (a) RBC static images (top row) compared to RBCsresponse using 0.0026 MHz/s (middle and bottom row). R1 and R2 are twodifferent repeats completed for this measurement. (b) nDEP and (c) pDEPintensity profiles for 0.0026 MHz/s with RBC static steady statemeasurements (circles). The images show poor agreement and intensityprofiles show good agreement with static measurements. Each test wascompleted with A+ blood in 0.10 S/m at 1000V_(pp)/cm.

FIG. 10 illustrates (a) RBC static images (top row) compared to theresponse of RBCs using a sweep rate of 0.0028 MHz/s (middle and bottomrow). R1 and R2 are two different repeats completed for thismeasurement. Panels (b) nDEP and (c) pDEP show intensity profiles for0.0028 MHz/s with RBC static steady state measurements (circles). Theimages show poor agreement and intensity profiles illustrate the lack ofreproducibility of agreement with static measurements. Each test wascompleted with A+ blood in 0.10 S/m at 1000V_(pp)/cm.

FIG. 11 illustrates (a) A− RBC static images (top row) compared to A−RBCs response using 0.0024 MHz/s (bottom row). (b) nDEP and (c) pDEPintensity profiles for 0.0024 MHz/s with RBC static steady statemeasurements (circles). The images and intensity profiles show goodagreement with static measurements. Each test was completed in 0.10 S/mat 1000V_(pp)/cm.

FIG. 12 illustrates (a) O+ RBC static images (top row) compared to O+RBCs response using 0.0024 MHz/s (bottom row). (b) nDEP and (c) pDEPintensity profiles for 0.0024 MHz/s with RBC static steady statemeasurements (circles). The images and intensity profiles show goodagreement at 0.70 MHz and fair agreement at 0.80 MHz. Each test wascompleted in 0.10 S/m at 1000V_(pp)/cm.

FIG. 13 illustrates (a) B+ RBC static images (top row) compared to OB+RBCs response using 0.0024 MHz/s (bottom row). (b) nDEP and (c) pDEPintensity profiles for 0.0024 MHz/s with RBC static steady statemeasurements (circles). The images and intensity profiles show goodagreement over the tested frequency range 0.60-0.84MHz. Each test wascompleted in 0.10 S/m at 1000V_(pp)/cm.

FIG. 14 shows a plot of sweep rate (MHz/s) as a function of conductivityof a solution. The plot points are a sweep rate at which the results fora given conductivity were no longer accurate. The plotted curve definesa threshold sweep rate. Thus, sweep rates above the threshold sweep ratefor a given concentration are too fast, and any sweep rate below thecurve may be used accurately and reliably. This aids in determining thefastest sweep rates that may be used for a solution with a givenconcentration in order to decrease the overall time needed for theprocedure.

FIG. 15 shows RBC static images (top row) compared to RBCs responseusing 0.0024 MHz/s (bottom row). Each test was completed with A+ bloodin 0.10 S/m at 1000V_(pp)/cm. This illustrates the visual similaritybetween the static response and response at this sweep rate at thesolution conductivity of 0.10 S/m.

FIG. 16 shows RBC static images (top row) compared to RBCs responseusing 0.0024 MHz/s (bottom row). Each test was completed with A+ bloodin 0.50 S/m at 1000V_(pp)/cm. This illustrates the visual similaritybetween the static response and response at this sweep rate at thesolution conductivity of 0.50 S/m.

FIG. 17 shows RBC static images (top row) compared to RBCs responseusing 0.0024 MHz/s (bottom row). Each test was completed with A+ bloodin 1.00 S/m at 1000V_(pp)/cm. This illustrates the visual similaritybetween the static response and response at this sweep rate at thesolution conductivity of 1.0 S/m.

FIG. 18 shows pDEP and nDEP plots of scaled intensity versus frequencyfor A+ blood in 0.25 S/m at 1000V_(pp)/cm. This plot generally shows the0.0027 MHz/s sweep rates near the threshold sweep rate for thisconcentration match the static frequency data well, but the 0.0028 MHz/ssweep rate begins to falter.

FIG. 19 shows RBC static images (top row) compared to RBCs responseusing 0.0027 MHz/s and 0.0028 Mhz/s (middle and bottom row). Each testwas completed with A+ blood in 0.25 S/m at 1000V_(pp)/cm. Thisillustrates the visual similarity between the static response and theresponse at a sweep rate near the threshold sweep rate for the givenconductivity of the solution.

FIG. 20 shows pDEP and nDEP plots of scaled intensity versus frequencyfor A+ blood in 0.5 S/m at 1000V_(pp)/cm. This plot generally shows the0.0029 MHz/s sweep rates near the threshold sweep rate for thisconcentration match the static frequency data well, but the 0.0030 MHz/ssweep rate begins to falter.

FIG. 21 shows RBC static images (top row) compared to RBCs responseusing 0.0029 MHz/s and 0.0030 Mhz/s (middle and bottom row). Each testwas completed with A+ blood in 0.50 S/m at 1000 V_(pp)/cm. Thisillustrates the visual similarity between the static response and theresponse at a sweep rate near the threshold sweep rate for the givenconductivity of the solution.

FIG. 22 shows pDEP and nDEP plots of scaled intensity versus frequencyfor A+ blood in 1.0 S/m at 1000V_(pp)/cm. This plot generally shows the0.0030 MHz/s sweep rates near the threshold sweep rate for thisconcentration match the static frequency data well, but the 0.0030 MHz/ssweep rate begins to falter.

FIG. 23 shows RBC static images (top row) compared to RBCs responseusing 0.0030 MHz/s and 0.0031 MHz/s (middle and bottom row). Each testwas completed with A+ blood in 1.00 S/m at 1000 V_(pp)/cm. Thisillustrates the visual similarity between the static response and theresponse at a sweep rate near the threshold sweep rate for the givenconductivity of the solution.

FIG. 24 shows RBC static images (top row) compared to RBCs responseusing a sweep rate of −0.0024 MHz/s (bottom row). Each test wascompleted with A+ blood in 0.10 S/m at 1000 V_(pp)/cm.

FIG. 25 shows pDEP and nDEP plots of scaled intensity versus frequencyfor A+ blood in 0.10 S/m at 1000 V_(pp)/cm using the reverse sweepmethod as illustrated by the images in FIG. 24.

FIG. 26 shows RBC static images (top row) compared to RBCs responseusing 0.0024 MHz/s (bottom row). Each test was completed with A+ bloodin 0.10 S/m at 1000 V_(pp)/cm.

FIG. 27 shows pDEP and nDEP plots of scaled intensity versus frequencyfor A+ blood in 0.10 S/m at 1000 V_(pp)/cm using the reverse sweepmethod as illustrated by the images in FIG. 26.

DETAILED DESCRIPTION

Before any embodiments of the invention are explained in detail, it isto be understood that the invention is not limited in its application tothe details of construction and the arrangement of components set forthin the following description or illustrated in the following drawings.The invention is capable of other embodiments and of being practiced orof being carried out in various ways. Also, it is to be understood thatthe phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting.

Alternating current (AC) dielectrophoresis (DEP) experiments forbiological particles in microdevices have typically been applied atfixed frequencies. Reconstructing the DEP response curve from staticfrequency experiments is laborious, but is important for ascertainingdifferences in dielectric properties of biological particles. Thedisclosed systems and methods, on the other hand, employ the novelconcept of sweeping the frequency as a function of time to rapidlydetermine the DEP response curve from fewer experiments. Homogeneous6.08 μm polystyrene (PS) beads were initially used as a model system todetermine whether sweeping the frequency would be a viable method forgenerating DEP responses and then to identify an optimal sweep rate.Subsequent experiments were performed using the sweep rate approach with−7 μm red blood cells (RBC) to verify that this approach would also workwith biological samples. A Au/Ti quadrapole electrode microfluidicdevice was used to separately subject particles and cells to 10V_(pp) ACelectric fields at frequencies ranging from 0.010-2.0 MHz over sweeprates from 0.00080 to 0.17 MHz/s. PS beads exhibited negative DEPassembly over the frequencies explored, likely due to Maxwell-Wagnerinterfacial polarizations. Results demonstrate that frequency sweeprates must be slower than particle polarization timescales; in someembodiments, sweep rates near 0.00080 MHz/s yielded DEP behaviors veryconsistent with static frequency DEP responses for both PS beads andRBCs, although higher sweep rates may also be employed.

Accordingly, disclosed herein are systems and methods for identifying aparticle using dielectrophoresis (DEP). Embodiments of the methods andsystems disclosed herein may be used to distinguish between differenttypes of particles based on differences in dielectric properties of theparticles. In various embodiments, the particles that are analyzed mayinclude polystyrene beads (e.g. for testing purposes) or cells such asblood cells; in particular, different subtypes of red blood cells (e.g.A+, A−, O+, O−, etc.) may be distinguished based on the surface chargedifferences of the red blood cell subtypes (e.g. due to differingantigens on the cell surfaces). In general, the particles may range insize from about 1-50 μm and should be detectable (e.g. through opticalor electrical means) using the particle detector (e.g. an imagingsystem).

A system according to embodiments of the invention may include amicrofluidic device (which in some embodiments may include an enclosedmicrofluidic chamber) having a microelectrode array disposed in thefluid path of the microfluidic device. In various embodiments, particlesare delivered to the vicinity of the microelectrode array using themicrofluidic device prior to data collection. In certain embodiments,data collection is performed in a “batch-wise” manner, i.e. a group ofparticles is delivered to the microelectrode array and fluid movement isthen stopped before data collection begins so that particle movementsthat are observed are due to dielectrophoresis.

The microelectrode array in one embodiment is a quadrapole arrangementas shown, for example, in FIGS. 1, 2, 4, and 5. In this arrangement fourelectrodes are arranged in an “X” with a gap in the center (FIG. 5).Other possible arrangements of electrodes include interdigitatedelectrodes, V-shaped electrodes, circular electrodes, and T-shapedelectrodes. In various embodiments, the electrodes are arranged so thatoppositely charged electrodes are not parallel to one another, as thiswould create uniform fields whereas other, non-parallel geometriescreate non-uniform electric fields. In general, the electrodes arearranged so that they create a spatially non-uniform field. Theelectrodes are attached to the bottom of the microfluidic device and theparticles that are delivered to the device are initially distributed inthe vicinity of the electrodes in a random arrangement (e.g. see upperleft panel of FIG. 2a ) before any electrical signal is applied. Themicroelectrode array may be made by depositing metal strips onto a glassslide with a cover having a microfluidic channel being bonded on top ofthe glass slide (FIG. 1c ). As shown in FIG. 1 c, opposing pairs ofelectrodes may be electrically coupled using copper wires, as shown,with the leads (i.e. ground and “hot” AC signal) of a signal generatorbeing connected to the copper wires. In various embodiments, pairs ofelectrodes may be electrically coupled as shown in FIG. 1c so that, uponstimulation, each electrode is 90° out of phase from the others tocreate a traveling wave signal.

Once particles have been delivered to the microelectrode array, a signalgenerator is used to deliver an oscillating voltage to the electrodes.In various embodiments, the voltage is applied at a peak-to-peakamplitude of 0.1V_(pp), 1V_(pp), 10V_(pp), 100V_(pp), or other suitableamplitude. In various embodiments, the oscillating voltage is applied atfrequencies of at least about 0.001 MHz, at least about 0.005 MHz, atleast about 0.01 MHz, at least about 0.05 MHz, at least about 0.1 MHz,at least about 0.5 MHz, or at least about 1.0 MHz. In other embodiments,the oscillating voltage is applied at frequencies of no more than about10.0 MHz, no more than about 5.0 MHz, no more than about 2.0 MHz, nomore than about 1.0 MHz, or no more than about 0.5 MHz.

In particular embodiments, the frequency of the oscillating voltage isvaried, for example from a low frequency to a high frequency, in orderto collect data at a variety of different frequencies, a processreferred to as “sweeping” the frequency. In various embodiments,comparable results are obtained when the frequency is swept from a highfrequency to a low frequency. Sweeping the oscillating voltage using acontinuously varying frequency permits a relatively large amount of datato be gathered in a short period of time. The rate at which thefrequency sweep, i.e. the “sweep rate,” may vary from 0.00001 MHz/s to0.1 MHz/s. In certain embodiments, the continuously varying frequencymay be approximated by a series of discrete, step-wise changes infrequency with an increment ranging from about 10 nHz to about 10 Hz. Asdiscussed herein, the optimum sweep rate may depend on conditions suchas the conductivity of the solution in which the particles aresuspended. The present inventors have found that when the frequency isswept above a certain maximum sweep rate the frequency changes tooquickly, such that the particles do not have sufficient time to respondto the voltage signal at a given frequency before the signal changes tothe next frequency. If the oscillating voltage signal is varied tooquickly, i.e. above the maximum sweep rate, the observed particlemovements and distributions will be inaccurate and could lead to aninconclusive or erroneous particle identification. Thus, in certainembodiments the maximum sweep rate is no more than about 0.003 MHz/s, nomore than about 0.0029 MHz/s, no more than about 0.0028 MHz/s, no morethan about 0.0027 MHz/s, no more than about 0.0026 MHz/s, no more thanabout 0.0025 MHz/s, no more than about 0.0020 MHz/s, no more than about0.0015 MHz/s, no more than about 0.0010 MHz/s, no more than about 0.0008MHz/s, or no more than about 0.0005 MHz/s. In various embodiments, aminimum sweep rate of at least about 0.00005 MHz/s, at least about0.0001 MHz/s, at least about 0.00015 MHz/s, at least about 0.0002 MHz/s,at least about 0.0004 MHz/s, at least about 0.0005 MHz/s, at least about0.00075 MHz/s, or at least about 0.0010 MHz/s may be used.

While the oscillating voltage is being applied to the microelectrodearray at varying frequencies, data may be collected to determine thespatial distribution of the particles within the microfluidic device,particularly the particles in the vicinity of the electrodes, as afunction of time. Particle detection may be carried out with systemswhich are capable of identifying the spatial distributions of theparticles with sufficient temporal (e.g. operating at 0.1-10 Hz) andspatial (e.g. capable of resolving 0.1 μm×0.1 μm areas) resolution.

In some embodiments, images are collected at regular intervals (e.g. atvideo rates of 30 frames/sec or at other, slower rates such as 1 imageor frame/sec) while sweeping the oscillating voltage. The images may beprocessed (for example several sequential video-rate frames may beaveraged together) and the images or subregions thereof may be analyzedto characterize particle distribution and behavior at one or severalfrequencies. The analyses may include one or more of determining theparticles' intensity profiles, transient responses, and velocities.Analyses may be conducted at one or more discrete locations within theimages including along one or more lines, e.g. lines running betweenelectrode tips. Analysis patterns for a sample which includes an unknownparticle may be compared to patterns generated under equivalentconditions using known particles to determine the identity of theunknown particle. In certain embodiments in which only a few (e.g. 2-3)types of particles need to be distinguished, it may be sufficient toanalyze only two subregions of the particle distribution in order toreliable distinguish the particle types from one another. In otherembodiments in which a larger number of particle types are possible itmay be necessary to analyze more subregions in order to reliablydistinguish among particle types. For example, in order to distinguishamong the eight red blood cell subtypes (A+, A−, B+, B−, O+, O−, AB+,and AB−) it may be necessary to analyze at least 4 different subregionsof the particle distribution, and greater accuracy would be achieved byincluding more of the particle distribution in the analysis. In general,regions and patterns on the substrate are selected for analysis based onthe areas that are expected to have the greatest change in electricfield patterns and hence the greatest change in particle distribution atdifferent frequencies, so as to provide the most information fordistinguishing between particle types. Additional methods for analyzingDEP behavior of particles are disclosed in Salmanzadeh et al. (2012),Rozitsky et al. (2013), and An et al. (2014), each of which isincorporated herein by reference.

A system for carrying out embodiments of the invention may include acontroller for carrying out or more of the procedures disclosed herein.The controller may be in operative communication with one or more of thesignal generator (which in turn is in communication with themicroelectrode array) and the particle detector (e.g. imaging system).The controller may be a part of or in communication with a computersystem. The computer system may be part of an existing computer system(e.g. on a smartphone, desktop computer, on-board computer, etc.) or maybe implemented as a separate, standalone unit that is in local or remotecommunication with other components. The computer system(s) may be inwired or wireless communication with other systems through a combinationof local and global networks including the Internet. Each computersystem may include one or more input device, output device, storagemedium, and processor (e.g. a microprocessor). Input devices may includea microphone, a keyboard, a computer mouse, a touch pad, a touch screen,a digital tablet, a track ball, and the like. Output devices include acathode-ray tube (CRT) computer monitor, an LCD or LED computer monitor,touch screen, speaker, and the like.

The computer system may be organized into various modules including anacquisition module and an output module along with the controller, wherethe controller is in communication with the acquisition module and theoutput module. The various modules for acquiring and processing data andfor returning a result may be implemented by a single computer system orthe modules may be implemented by several computer systems which are ineither local or remote communication with one another.

Storage media include various types of local or remote memory devicessuch as a hard disk, RAM, flash memory, and other magnetic, optical,physical, or electronic memory devices. The processor may be any knowncomputer processor for performing calculations and directing otherfunctions for performing input, output, calculation, and display of datain accordance with the disclosed methods. In various embodiments,implementation of the disclosed invention includes generating sets ofinstructions and data that are stored on one or more of the storagemedia and operated on by a controller, where the controller may beconfigured to implement various embodiments of the disclosed invention.

Some embodiments the system may be in the form of a portable or handhelddevice which may be self-contained, including the microfluidic device,microelectrode array, the controller, and additional components such asa power supply and input/output capabilities.

Without being limited as to theory, DEP enables phenotypically similarbiological cells to be discriminated based on dielectric propertiesincluding the conductivity and permittivity of the membrane, cytoplasm,and other structurally relevant organelles. Cell components andstructure contribute to a cell's signature dielectric dispersion. Aparticle's complex permittivity is frequency dependent and characterizedby dielectric dispersion regions (y, β, and α, where w_(α)<w_(β)<w_(y))specific to an applied frequency. Certain embodiments of this work toillustrate sweep rates uses frequencies in the range of 0.010 to 2.0 MHzin the β-dispersion region because the Clausius-Mossotti factor, whichgoverns sign and polarization strength, for polystyrene beads is nearlyconstant over this range. Maxwell-Wagner theory describes thepolarization mechanism of particles in the β-dispersion region asinterfacial polarization where moving charges build around the interfaceof a charged or charge-neutral particle and exchange ions with thesuspending medium. Interfacial particle polarization creates an induceddipole moment such that the particle experiences disproportionate forcesin each half cycle of the alternating current (AC) field resulting innet particle movement.

Polarized particles can exhibit either positive dielectrophoresis (pDEP)or negative dielectrophoresis (nDEP) as a consequence of thefrequency-dependent polarizability of the particle in the surroundingmedium. Particles that exhibit pDEP move to high electric field regionsand particles that exhibit nDEP move to low electric field regions. Thismotion up and down electric field gradients is described by theClausius-Mossotti factor for spherical particles.

${f_{cm} = \frac{{\overset{\sim}{ɛ}}_{p} - {\overset{\sim}{ɛ}}_{m}}{{\overset{\sim}{ɛ}}_{p} + {2{\overset{\sim}{ɛ}}_{m}}}},{{\overset{\sim}{ɛ}}_{i} = {{\overset{\sim}{ɛ}}_{i} + \frac{\sigma_{i}}{\omega \; j}}},$

where {tilde over (ϵ)}_(i) is the complex permittivity of the particle(i=p) and of the medium (i=m), which are both functions of conductivity(σ), permittivity (ϵ), and angular frequency (ω).

Polarization is not an instantaneous event; charge transport into theinterface takes a few microseconds in response to the electric field.Maxwell-Wagner dielectric relaxation is a physical phenomenon related tothe transport delay of cation and anion alignment in and around theinterface of the dielectric particle. At lower frequencies (<˜10 MHz),particle polarization is driven by this conductive polarization. Athigher AC frequencies, charges do not have enough time to move into andaround the interface double layer, so particles experience polarizationlag time as a result of the rapidly modulating field and do not reachmaximum polarization.

Maxwell-Wagner dielectric relaxation is characterized by a timeconstant, τ_(MW), which is unique to each particle or cell due to thetime constant's dependence on the cell dielectric properties. The timerequired for a particle to reach maximum polarization is given by Eq.(3) (see Morgan et al. (2003), p. 27; see also Grosse et al. (2010) andMittal et al. (2008), each of which is incorporated herein byreference):

$\tau_{TW} = {\frac{\left( {ɛ_{p} + {2ɛ_{m}}} \right)ɛ_{0}}{\sigma_{p} \pm {2\; \sigma_{m}}}.}$

Typical relaxation times for particle polarization vary from pico- tomicroseconds (see Morgan et al. (2003), p. 27; see also Grosse et al.(2010) and Mittal et al. (2008)), and the calculated τ_(MW) forpolystyrene (PS) beads in our Epure H₂O medium at 2.5×10⁻⁴ S/m is 3.5las. Thus, a single AC cycle is on the order of 0.01 to 2μs; the timedelay in ion transport within a static frequency field of 0.010 to 2.0MHz is such that 2 to 350 AC cycles must be completed before theparticle experiences full polarization.

The Maxwell-Wagner dielectric timescale for charge transport into andaround the interface becomes important when the frequency is swept, i.e.changes as a function of time. FIG. 1a highlights the Maxwell-Wagnerparticle polarization at the interface under static frequency as well asslow and fast frequency sweep rates. At a static frequency in theβ-dispersion region, the particle experiences a constant frequency fieldsuch that the relaxation time is not a factor and the particle fullypolarizes. A particle in a field with a slowly changing frequency sweephas a relaxation time, τ_(ΔFS), that is less than τ_(MW) and thus theparticle interface fully polarizes. Tn contrast, a particle in a fastfrequency sweep has a relaxation time, τ_(ΔFS), that is larger thanτ_(MW) and the particle interface does not have time to fully polarizein the field. PS beads are lossy dielectric particles treated ashomogeneous spheres and are thus an idealized particle to examine newtechniques, devices, or approaches to dielectrophoreticcharacterizations. Our system is easily able to discern pDEP and nDEPtransitional behavior and adaptable to new frequency sweep techniques.The homogeneous spherical DEP polarization model for PS beads (ϵ=2.5 andσ=9.4×10⁻⁵ S/m) suspended in Epure H₂O displays only nDEP behavior over0.010 to 2.0 MHz.

Thus, microfluidic and dielectrophoretic (DEP) technologies enable awide variety of particle polarizations with nonuniform electric fieldson microchips to achieve particle manipulation, concentration,separations, and property-based identification. Particles can includebioparticles (e.g. DNA, viruses, or proteins) as well as cells (e.g.blood cells, cancer cells, stem cells, and yeast). The advantages tocoupling DEP with microfluidics are small sample size (on the order ofmicroliters), rapid analysis (approximately minutes to achieve results),minimal sample preparation, and minimal waste production. Traditionally,DEP experiments are completed at static, fixed frequencies such thatmaximum particle polarization can be achieved and measured. Multipleexperiments are conducted, each at discrete frequencies over the rangeof interest to stitch together DEP response spectra; this is alabor-intensive approach. Further disadvantages are that extended fieldexposure times at fixed frequencies can change particle properties orcell viability. As disclosed herein, it is demonstrated that frequencycan be swept with time in the β-dispersion region thus enablinginterrogation of cells at multiple frequencies within a short timeperiod. The benefits of using a frequency sweep technique are thatnearly continuous DEP response curves, when coupled with automatedresponse analysis, can be compiled in near real time and the number ofexperiments needed to obtain particle DEP spectra are greatly reduced.

Traditional DEP measurements are completed at single static frequenciesin order to compile frequency by frequency, the DEP spectrum for aparticle or cell system. This method is laborious and, as disclosedherein, requires time for particles to fully polarize for accurateobserved DEP responses. The present disclosure describes the use offrequency sweeps as a means to more efficiently interrogate multiplefrequencies in a single experimental run and systematically compared theresponses to the nDEP response at fixed frequencies between 0.010 and2.0 MHz. It was observed that frequency sweep rates influence the DEPresponse of PS beads and RBCs and further, the permissible frequencysweep rate is particle or cell dependent. The underlying mechanismappears to be the same. At slower sweep rates, particles have more timeto polarize in the electric field and therefore a more accurate andreproducible DEP spectrum can be obtained. At faster frequency sweeprates, the particles are unable to achieve maximum interfacialpolarization because of the dielectric relaxation time scale so theobserved DEP response does not match the true DEP behavior of theparticle.

For polystyrene beads at frequency sweep rates below 0.0063 MHz/s,responses correlate closely with dielectric responses of particlessubjected to a static frequency potential. In the PS bead system, 0.056MHz/s is the transitional sweep rate where the particle dielectricrelaxation is approximately the same order of magnitude as the shifts infrequency within the sweep. Dielectric responses continue to track thestatic frequency responses, although reproducibility is diminished.However as this sweep rate is increased further, conductivity dominatedinterfacial polarizations cannot be established and the PS beadfrequency sweep data does not coincide with static frequencymeasurements.

For full utility in DEP experiments, this frequency sweep ratemethodology must be translatable to cell systems. Results illustratedthat only 0.00080 MHz/s accurately predicted the static frequency DEPresponses of human RBCs. Red blood cells are substantially moremorphologically and dielectrically complex than polystyrene beads.Calculation of the dielectric relaxation time, taking into account onlythe membrane permittivity and conductivity of 4.4 and 10⁻⁷ S/m,respectively (Gascoyne et al. (2004), incorporated herein by reference)yields a dielectric relaxation time ˜4.6 μs roughly corresponding to0.21 MHz. This relaxation time is larger than the PS bead relaxationtime of 3.5 μs, so the optimal frequency sweep rate for red blood cellswould be slower than that for PS beads. This result suggests that foreach new cell system of interest it is imperative to determine theoptimal frequency sweep rate for accurately and reproduciblyinterrogating the behavior of that cell. This work outlines a systematictechnique to make comparisons between frequency sweep rate and staticfrequency shown. For all cell systems, sweep rates that are too fastwill not allow the cell adequate time to polarize and will result ininaccurate and less reproducible DEP responses. An optimal frequencysweep rate can be estimated by calculating the Maxwell-Wagner dielectricrelaxation time for the particle/cell of interest, provided the cell'spermittivity and conductivity is known. The frequency sweep rate chosenfor the DEP study should then remain at frequencies below the inversedielectric relaxation time (1/τ_(MW)) for 5-45 s (longer times spentbelow the threshold give better DEP predictions).

Since the cell's permittivity and conductivity are determined from thefrequency dependent DEP spectrum, this presents a cyclical situation.However, this work has demonstrated that frequency sweep rates slowerthan 0.00080 MHz/s can yield accurate DEP response of PS beads as wellas RBCs. This sweep rate may therefore be translatable to other cellsystems. In addition, at higher frequencies where the polarizationmechanism is more heavily influenced by charge permittivity effectsthrough the membrane and cell cytosol, it is possible that slowfrequency sweep rates can still accurately capture DEP response spectra.Lastly, this frequency sweep rate technique will enable researchers toobtain accurate and continuous DEP response spectra in shorterexperiment times.

The following non-limiting Examples are intended to be purelyillustrative, and show specific experiments that were carried out inaccordance with embodiments of the invention.

EXAMPLES Example 1

In this Example, dielectrophoretic responses of PS beads (model system)were quantified at both static frequencies and frequency sweeps at ratesranging from 0.00080 to 0.17 MHz/s over the β-dispersion frequency rangeof 0.010-2.0 MHz. PS bead motion in the electric field was imaged withvideo microscopy and analyzed using three techniques: intensityprofiles, transient response, and particle velocities. Data shows thatfrequency sweep rates impact particle polarization due to dielectricrelaxation limitations. This frequency sweep technique was furtherextended in this Example to negatively charged biconcave red blood cells(RBCs), which are an important cellular system for medical diseasediagnostics.

The microdevice shown in FIG. 1c was fabricated according to previouslypublished microfabrication techniques (Grom et al. (2006), incorporatedherein by reference), with the 100 μm wide electrodes spaced 200 μmapart aligned at 90° along the bottom of a 70 pm deep by 1000 μm widemicrofluidic chamber as shown in FIG. 1 b. Polystyrene beads (Cat No.PP-60-10, Spherotech, Lake Forest, Ill., USA), 6.08 μm in diameter werecentrifuged at 1300 min⁻¹ for 5 mins to separate the beads from theliquid. The PS beads were resuspended in Epure H₂O (18 MΩ or 2.5×10⁻⁴S/m) at a 1:10 (bead to water) volumetric dilution ratio and vortexed.Microdevice was pre-rinsed with Epure H₂O and Alconox precision cleaner(Cat No. 1104, Alconox Inc, White Plains, N.Y., USA) to prevent beadadhesion. PS beadEpure H₂O suspension was pumped to the microchamberusing a syringe. Time was allowed for inlet and outlet pressures toequalize and flow to stop. The function generator (Agilent 33250A,Agilent, Santa Clara, Calif., USA) was connected via copper leads toproduce a 10V_(pp) AC sine wave with frequencies ranging from 0.010-2.0MHz at specific frequency sweep rates 0.00080, 0.0011, 0.0030, 0.0063,0.013, 0.021, 0.028, 0.042, 0.056, 0.083, and 0.17 MHz/s. Frequencysweeps linearly increased the applied frequency as a function of time.Greater than five (n>5) static frequency experiments were completed ateach frequency 0.010, 0.020, 0.030, 0.040, 0.050, 0.20, 0.40, 0.60,0.80, 1.0, 1.2, 1.4, 1.6, 1.8, and 2.0 MHz by applying 10V_(pp) for 90s. These DEP static frequency responses were compared to each frequencysweep rate DEP responses. For the static and frequency sweepexperiments, the PS bead concentration was between 238-263 beads in thet=0 field of view. Video recordings of experiments were taken at 30 fpsat 640×480 pixels/image using LabSmith SVM Synchronized Video Microscopewith a 10× objective (LabSmith, Livermore, Calif., USA).

Video recordings of PS beads DEP behaviors were analyzed with ImageJ(NIH, Bethesda, Md.) using intensity, transient slope, and velocitymeasurements. Since PS beads only exhibit nDEP over the frequency rangeof interest, intensity data acquisition from images was completed bydrawing a rectangular box at the device center, I_(CTR), and background,I_(BK) measured in a location with no PS beads present (See FIG. 2a ).ImageJ Z Project function was used to average the pixel intensities inthe specified boxed region. The initial background, I_(BK)(t=0) andcenter intensity, I_(CTR)(t=0) were subtracted from the center andbackground intensity at each time, I_(CTR)(t) and I_(BK)(t), and then anormalized intensity was calculated by dividing by the maximum intensityexperienced by the PS beads, (Eq. (4)):

${\overset{\_}{I}}_{{DEP},t} = \frac{\left\lbrack {\left( {I_{CTR} - I_{BK}} \right)_{t} + \left( {I_{BK} - I_{CTR}} \right)_{t = 0}} \right\rbrack}{\left\lbrack {\left( {I_{CTR} - I_{BK}} \right)_{t} + \left( {I_{BK} - I_{CTR}} \right)_{t = 0}} \right\rbrack_{MAX}}$

This normalized intensity tracked the real-time magnitude of the PS beadDEP response, which had two distinct regions: transient where beadsmoved with nDEP toward the center, and steady-state (SS) where beadsachieved tight packing at the device center. These two responses wereanalyzed separately via transient slope and particle velocity.

The transient response of the PS beads was extracted from thesteady-state response via signal processing in which the delay and risetime were quantified. The PS bead delay time, t_(d), was characterizedas the time required for the intensity response to reach 50% of thefinal intensity response for the first time. The rise time, t_(T), wasdetermined as the time needed for the intensity response to reach 100%of the final intensity response for the first time (Ogata et al. (1978),pp. 517-518, incorporated herein by reference). This allowed thetransient response to be segmented and a linear trend line was fitbetween t_(d) and t_(T) where t_(d)<t_(T). A comparison of the transientslope for frequency sweep rates and static frequency measurements isgiven in FIG. 3c . PS bead velocities were determined from the originalvideo by tracking the x-, y-pixel position of individual PS beads from0-50 s. PS bead located within 5 μm of electrode tips were selected tocontrol for similar electric field gradients. This procedure wasrepeated for at least 10 beads in each specific frequency sweep rate andstatic experimental video.

For experiments involving human RBCs, blood of the appropriate type(e.g. O+, A+, etc.) was obtained from a single donor and centrifuged at1400 rpm for 5 mins to separate the packed RBCs from the plasma andleukocytes. The packed RBCs were removed, then resuspended at 1:75 v:vin 0.10 S/m isotonic dextrose buffer doped with 0.75% BSA (Cat No.A7906, Sigma Aldrich, St. Louis, Mo., USA) to prevent cell/deviceadhesion. This RBC suspension was syringe-pumped to the microchamber,with time being allowed for flow to stop after pumping before the10V_(pp) signal was applied over 0.010-0.50 MHz (range reduced to avoidpDEP behavior) at frequency sweep rates of 0.00080, 0.0063 and 0.056MHz/s (n=7). RBC static frequency experiments were completed at 0.010,0.10, 0.25 and 0.50 MHz at 10V_(pp) for 90 s (n=7). Video microscopy at25× and 1 fps was obtained with a Zeiss Axiovert Inverted LightMicroscope (Zeiss, Germany). The video images were analyzed as describedherein for the PS beads.

Frequency sweep rates ranging from 0.00080 to 0.17 MHz/s were exploredto see if the nDEP response of PS beads would vary and/or correspond tostatic frequency measurements. The frequency range was chosen for therelatively consistent Clausius-Mossotti factor, Re(f_(CM)) for ahomogeneous lossy polystyrene sphere of 0.26 to 0.48 (see FIG. 2c ) overthe frequency range of 0.010 to 2.0 MHz. Static frequency experimentswere completed at fixed values in this same frequency range. FIG. 2ashows still images from both static frequency experiments and thefrequency sweeps at 0.20, 0.60, and 1.0 MHz. For static frequencies, theresponse 45 seconds after field application is shown while for frequencysweeps of 0.0063, 0.056, and 0.17 MHz/s, the image is shown at the timestamp when the specified frequency is reached. The electrodes arevisible as black shadows in the images and the PS beads assemble due tonDEP forces at the central electric field gradient minima Data wasexamined to determine the sweep rate that most closely approximated thestatic frequency response. Frequency sweeps 0.00080 and 0.0063 MHz/s(shown) tracked static frequency, or true, DEP responses while theslightly faster sweep of 0.056 MHz/s begins to lag the true DEPresponses and at 0.17 MHz/s and faster, particles were unable to achievesufficient polarization to respond sufficiently in the electric field.

nDEP responses were quantified via intensity analysis as describedherein for all sweeps and all static frequency experiments. FIG. 2billustrates the frequency- (and time-) dependent intensity for the0.0063 MHz/s sweep rate images shown in FIG. 2a . This quantification ofthe PS bead nDEP response was correlated to total bead packing via thecalibration shown in the inset. The 188-bead count at the centerdeviates slightly from the initial, field off, bead count of 245 becausePS beads also move down the electric field gradient to regions outsideof the image field of view.

Normalized intensities, Eq. (4), were compiled in FIG. 3a for SS (i.e.45 seconds) static frequency nDEP responses and 0.00080, 0.0063, 0.056MHz/s frequency sweep rate nDEP responses. The time for sweep responsesto achieve the true nDEP static response decreases as the sweep ratedecreases. Frequency sweep rates 0.00080 and 0.0063 MHz/s are within the95% confidence intervals (n=7) of the static steady-state (SS)responses. FIG. 3a inset shows that the slowest 0.00080 MHz/s sweep ratemore quickly aligns closely with the static frequency responses. FIG. 3bcompares average 0.0063 MHz/s (n=8) to 0.17 MHz/s (n=7) with the dashedlines signifying the upper and lower limits of the 95% confidenceintervals for I_(DEP). The confidence intervals around the transient0.0063 MHz/s sweeps are smaller than for 0.17 MHz/s over much of thefrequency range indicating greater reproducibility at slower sweeprates. Faster sweep rates either do not reach SS or have a lag beforereaching SS (compare to FIG. 2a ) suggesting the bead interface does notfully polarized and thus displays attenuated nDEP motion.

The transient behavior was quantified for all static frequencies andfrequency sweeps via a transient slope analysis as compiled in FIG. 3c .Four static frequency measurements 0.010, 0.60, 1.0 and 2.0 MHz areshown compared to 0.00080, 0.0063, 0.028, 0.056, and 0.17 MHz/sfrequency sweep rates. Static frequency transient slopes range between0.023-0.095 and are within the 95% (p<0.05) confidence intervals of0.00080, 0.0063, and 0.028 MHz/s frequency sweep transient slopes. Theseslower sweep rates and 0.056 MHz/s differ at p<0.001 from the fastestsweep rate of 0.17 MHz/s, which is also significantly different atp<0.001 from the static measurements (except for 1.0×10⁴ Hz withp<0.01).

Individual bead velocities were compiled for static as well as frequencysweeps in FIG. 3d . PS bead velocity corroborates the intensity profileand the slope analysis that 0.00080 MHz/s frequency sweep rate closelytracks the bead velocity at static frequencies. 0.056 MHz/s gives goodestimations of static frequency bead velocity at times greater than 20s. Based on intensity, transient slope, and velocity analysis, the slowfrequency sweep rate of 0.00080 MHz/s is most consistent with staticfrequency DEP responses.

There is an observable inverse relationship between the frequency sweeprate and particle polarization, where slower sweep rates result incomparable particle polarization characteristics to static frequencyresponses. Dielectric relaxation is the driving force of thisrelationship; the calculated dielectric relaxation time Eq. (3) for PSbeads in E-pure H₂O at 2.5×10⁻⁴ S/m is 3.5 ps, which corresponds to 0.28MHz. There are two timescales that influence this behavior: thefrequency itself and the change in frequency per time. TheMaxwell-Wagner, conductivity-driven interfacial polarization mechanismoccurs below ˜0.28 MHz; above this frequency threshold the interfacialpolarization of the PS beads gradually decreases and the particlepermittivity increasingly influences the DEP force. The experimentalfrequencies tested were within the range dominated by Maxwell-Wagnerpolarization such that maximum particle interfacial polarization waspossible.

The second timescale of interest is the frequency change per time orfrequency sweep rate, which determines how many consecutive cycles aparticle experiences a specific frequency. At slower sweep rates, the PSbeads experience a specific frequency for a large number of cycles andthus the beads have time to polarize because the timescale of thefrequency change is slower than the dielectric relaxation time. Aparticle must experience a single frequency during the sweep for aminimum of 3.5 μs for maximum interfacial polarization to be achieved.Upon polarization, the particle, which its current DEP force has toovercome inertia and Stokes drag to achieve observable particle motiondown the electric field gradient. At static frequencies, it takesroughly 5 s for maximum velocity to be attained (see FIG. 3d , AC fieldapplied at t=5 s) and as much as 45 s for final SS at the field gradientminima to be reached. As the sweep rate increases, the dielectricrelaxation time and the rate of change of the frequency approach thesame order of magnitude. Results suggest that 0.056 MHz/s is atransitional sweep rate because the DEP behavior roughly corresponds tothe static behavior of the PS beads. With further increases in frequencysweep rates, the timescale for frequency change surpasses the dielectricrelaxation timescale such that particles are unable to fully polarizeresulting in an attenuated DEP response as shown with data in FIGS. 2, 3a, and 3 b. FIG. 3b also demonstrates that the transient behavior of thePS beads is more reproducible at slower frequency sweep rates, which canbe attributed to the interfacial polarization timescale of the beads.Implications of the intensity, slope, and velocity analysis comparedwith static frequencies are that slow frequency sweep rates accuratelypredict the DEP response of PS beads because the changes in frequencyare slower than the characteristic Maxwell-Wagner dielectric relaxation.

Thus, a frequency sweep approach can be utilized to attain accurate DEPbehavior of PS beads, provided the sweep rate is slower thanconductivity mediated interfacial polarization timescale. This result isreliable over frequency ranges where particle polarization is dominatedby the conduction of free charges from the media. The charges are movingaround the PS beads through the particle-liquid interface inducing adipole, which causes PS bead movement down the electric field gradientto the electrode center. At different sweep rates the rate of movementof the charges varies which varies the rate of the dipole being induced,observed as dielectric relaxation. Each sweep rate has a uniquedielectric relaxation time and our results are consistent withMaxwell-Wagner interfacial polarization theory. 0.00080 MHz/s is theoptimal sweep rate necessary to predict the true DEP behavior of PSbeads because it allows for full or partial (when the frequency is above0.28 MHz) polarization.

Given that the sweep methodology yielded accurate DEP responses for theideal system of PS beads, the same methodology and frequency sweep rateswere explored with human RBCs. The three most successful PS beadfrequency sweep rates were reproduced with human red blood cells:0.00080 MHz/s, 0.0063 MHz/s and 0.056 MHz/s. Static frequencyexperiments were also performed at 0.010 MHz, 0.10 MHz, 0.25 MHz and0.50 MHz. Seen in FIG. 4a are 25× microscope images taken of the t=45 sfinal static frequency frames aligned above the sweep time points thatcorrespond to those four static frequencies. Qualitatively, the onlysweep rate that accurately matches the static frequency behavior of thehuman RBCs is 0.00080 MHz/s. This behavior was further verified by thesame intensity analysis as for PS beads. In FIG. 4b , the scaledintensity is plotted for 0.00080, 0.0063 and 0.056 MHz/s experiments(n=8) as compared to the static frequency intensities. After the initial10 s transition for the red blood cells to polarize and overcome drag,the slowest frequency sweep of 0.00080 MHz/s accurately predicts thestatic frequency behavior and is highly reproducible, with a very narrow95% confidence interval range (FIG. 4c ). The fastest sweep rate of0.056 MHz/s does not predict the static behavior of the human RBCs andis much less reproducible, as evidenced by the large 95% confidenceinterval in FIG. 4c . From these experiments, we conclude that theoptimal frequency sweep for determining the accurate DEP behavior ofRBCs is 0.00080 MHz/s. Due to the complex dielectric properties ofcells, it is necessary to carefully compare frequency sweep rates withstatic frequency behaviors to ascertain optimal frequency sweep ratesthat accurately interrogate the cell of interest.

Example 2

Conditions for Example 2 are the same as described above for Example 1except where otherwise stated. FIGS. 5-13 show data obtained fromapplying a sweeping oscillating voltage signal of 1000Vpp/cm to humanred blood cells in a solution with conductivity of 0.10 S/m. FIGS. 5-10show data obtained from A+ RBCs while FIG. 11 shows data from A− RBCs,FIG. 12 shows data from O+ RBCs, and FIG. 13 shows data from B+ RBCs.

FIG. 5 shows images of A+RBCs distributed in the vicinity of quadrapoleelectrodes during application of an oscillating voltage havingfrequencies ranging from 0.01 MHz to 1.0 MHz applied statically or atsweep rates of 0.00080 MHz/s, 0.0016 MHz/s, or 0.0028 MHz/s. Thenotation “(1)” denotes RBCs demonstrating nDEP behavior and “(2)”denotes RBCs demonstrating pDEP behavior. The RBC's DEP behavior atslower frequency sweep rates (0.00080 MHz/s and 0.0016 MHz/s) correlateswell with the static frequency response (top row), indicating that theseare below the maximum sweep rate for these conditions. FIG. 6 comparesthe nDEP (panel (a)) and the nDEP (panel (b)) intensity profiles of theparticles for the statically applied oscillating voltage as well as atthe various sweep rates tested across the range of frequencies.

Panel (a) of each of FIGS. 7-13 shows images of particle distributionsat oscillating voltages of 0.70 MHz and 0.80 MHz collected either withstatic application of the oscillating voltage (“0 MHz”) or whilesweeping at the indicated sweep rates. Panels (b) and (c) of each ofFIGS. 7-13 show nDEP (panels (b)) and pDEP (panels (c)) intensityprofiles throughout the frequency range relative to intensity profilesobtained with statically-applied oscillating voltages at 0.7 MHz and 0.8MHz. FIGS. 7-10 include results from two different experimental runs, R1and R2.

Comparison of the images of particle distributions at different sweeprates relative to distributions obtained with statically appliedoscillating voltages provides an indication of whether or not the sweeprate is too fast, based on whether the swept images match those obtainedwith statically applied oscillating voltages at the same frequency.

The data in this example shows the applicability of the disclosedmethods and in particular the similarity in maximum sweep rates forvarious blood types. The data also shows the dependence of the maximumsweep rate on conductivity of the solution in which the particles (RBCs)are suspended.

Example 3

Conditions for Example 3 arc the same as described above for Examples 1and 2 except where otherwise stated.

One factor which may affect the maximum sweep rate is the conductivityof the solution in which the particles are suspended. Accordingly,experiments were carried out to determine the extent to whichconductivity impacts the maximum sweep rate.

FIGS. 14-23 show the effect of changes in conductivity on the maximumsweep rate using red blood cells. When using biological material, and inparticular cells such as red blood cells, it is important when varyingthe conductivity of the solution to maintain the overall tonicity of thesolution within a limited range. For the experiments in FIGS. 14-23,varying combinations of NaCl and dextrose were combined to achieve thestated levels of conductivity of 0.10 S/m, 0.25 S/m, 0.50 S/m, and 1.0S/m while maintaining the solution at approximately isotonic levels forhuman red blood cells; increasing the amount of NaCl increases theconductivity and proportionately less dextrose is used as NaCl isincreased in order to maintain a relatively constant tonicity (see An etal. 2014, incorporated herein by reference).

As shown in FIG. 14, increasing conductance from 0.10 S/m to 1.0 S/m hasthe effect of increasing the maximum sweep rate that can be used fromless than 0.0026 MHz/s at 0.1 S/m to less than 0.0031 MHz/s at 1.0 S/m.As seen in FIGS. 15-23, using a sweep rate below the maximum levelgenerates particle distributions at various frequencies that areequivalent to distributions that are obtained with the application of anoscillating voltage at a static frequency. Increasing the conductancepermits the use of a faster sweep rate, which in turn permits data to becollected at a faster rate.

Example 4

Conditions for Example 4 are the same as described above for Examples1-3 except where otherwise stated.

The experiments of Example 4 demonstrate that particle DEP behavior isindependent of the ‘direction’ of sweeping, i.e. sweeping theoscillating voltage signal from a high frequency to a low frequencygenerates equivalent results as when the oscillating voltage is sweptfrom a low frequency to a high frequency.

FIG. 24 shows RBC static images (top row) compared to RBCs responseusing a sweep rate of −0.0024 MHz/s (bottom row). Each test wascompleted with A+ blood in 0.10 S/m at 1000 V_(pp)/cm. FIG. 25 showspDEP and nDEP plots of scaled intensity versus frequency for A+ blood in0.10 S/m at 1000 V_(pp)/cm using the reverse sweep method as illustratedby the images in FIG. 24.

FIG. 26 shows RBC static images (top row) compared to RBCs responseusing 0.0024 MHz/s (bottom row). Each test was completed with A+ bloodin 0.10 S/m at 1000 V_(pp)/cm. FIG. 27 shows pDEP and nDEP plots ofscaled intensity versus frequency for A+ blood in 0.10 S/m at 1000V_(pp)/cm using the reverse sweep method as illustrated by the images inFIG. 26.

REFERENCES

Each of the following references is incorporated herein by reference inits entirety:

A. Salmanzadeh, L. Romero, H. Shafiee, R. C. Gallo-Villanueva, M. A.Stremler, S. D. Cramer and R. V. Davalos, Lab on a Chip 12, 182 (2012).

L. Rozitsky, A. Fine, D. Dado, S. Nussbaum-Ben-Shaul, S. Levenberg, G.Yossifon, Biomed Microdevices 15, 859 (2013).

R. An, D. O. Wipf, A. R. Minerick, Biomicrofluidics 8, issue 2, article021803 (2014).

H. Xie, R. Tewari, H. Fukushima, J. Narendra, C. L. Heldt, J. King, A.Minerick, J. Vis. Exp. 88, e51696 (2014).

F. Grom, J. Kentsch, T. Muller, T. Schnelle, and M. Stelzle,Electrophoresis 27, 1386 (2006).

C. Grosse and A. V. Delgado, Current Opinion in Colloid & InterfaceSciences 15, 145 (2010).

H. Morgan and N.G. Green, R. Pethig, AC Electrokinetics: colloids andnanoparticles (Research Studies Press Limited, Philadelphia, 2003).

M. Mittal, P. P. Lele, E. W. Kaler, and E. M. Furst, Journal of ChemicalPhysics 129, 065413 (2008).

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P. Gascoyne, J. Satayavivad, and M. Ruchirawat, Acta Tropica 89, 357(2004)

Various features of the invention are set forth in the following claims.

1. A system for identifying a plurality of particles suspended in asolution, the system comprising: a microfluidic device to receive thesolution including the plurality of particles; a microelectrode arraycomprising a plurality of electrodes, the microelectrode array disposedwithin the microfluidic device and in vicinity of the received solution,the microelectrode array including a first plurality of electrodes toprovide a first charge and a second plurality of electrodes to provide asecond charge, the second charge being different than the first charge,and the second plurality of electrodes being in a nonparallelrelationship with the first plurality of electrodes; a signal generatoroperatively coupled to the microelectrode array; a particle detectoradjacent to the microelectrode array; and a controller in operativecommunication with the signal generator and the particle detector, thecontroller being configured to apply an oscillating voltage signal tothe microelectrode array at a plurality of frequency levels varyingcontinuously between a low frequency and a high frequency, the pluralityof frequency levels being applied at a sweep rate, wherein the sweeprate is no more than a maximum sweep rate and is no less than a minimumsweep rate, the applying of the oscillating voltage signal to themicroelectrode array resulting in a spatially non-uniform field, anddetermine a distribution of the plurality of particles relative to themicroelectrode array at the plurality of frequency levels varyingcontinuously between the low frequency and the high frequency.
 2. Thesystem of claim 1, wherein the solution has a conductivity and whereinthe maximum sweep rate is a function of the conductivity.
 3. The systemof claim 2, wherein the conductivity is 0.10 S/m and the maximum sweeprate is less than 0.0026 MHz/s.
 4. The system of claim 2, wherein theconductivity is 1.0 S/m and the maximum sweep rate is less than 0.0031MHz/s.
 5. The system of claim 1, wherein the low frequency is 0.01 MHzand the high frequency is 2.0 MHz.
 6. The system of claim 1, wherein theparticle detector comprises an image detector and an image analysissystem and wherein the controller, to determine the distribution of theplurality of particles relative to the microelectrode array, is furtherconfigured to collect an image of the microelectrode array using theimage detector and determine a spatially resolvable concentration of theplurality of particles relative to the microelectrode array using theimage analysis system at each of the plurality of frequency levels. 7.The system of claim 1, wherein, to determine the distribution of theplurality of particles relative to the microelectrode array, thecontroller is further configured to use an image analysis system todetermine a first spatial distribution of the plurality of particles anda second spatial distribution of the plurality of particles at a secondlocation at each of the plurality of frequency levels.
 8. The system ofclaim 7, wherein, to determine the first spatial distribution of theplurality of particles at a first location, the controller is furtherconfigured to use the image analysis system to determine an intensity ofthe plurality of particles at the first location.
 9. The system of claim7, wherein, to determine the second spatial distribution of theplurality of particles at the second location, the controller is furtherconfigured to use the image analysis system to determine an intensity ofthe plurality of particles at the second location.
 10. The system ofclaim 1, wherein the microelectrode array is a quadrapole microelectrodearray.
 11. The system of claim 1, wherein the plurality of particlescomprise red blood cells.
 12. The system of claim 1, wherein the sweeprate is no less than the minimum sweep rate.
 13. The system of claim 12,wherein the minimum sweep rate is 0.0008 MHz/s. 14-30. (canceled) 31.The system of claim 1, wherein the system comprises a handheld device,the handheld device including the microfluidic device, themicroelectrode array, the signal generator, the particle detector, andthe controller.